Donor Governance and Financial Management
in Prominent U.S. Art Museums
David Yermack
Department of Finance, NYU Stern School of Business
and National Bureau of Economic Research
dyermack@stern.nyu.edu
This draft: September 12, 2015
Abstract
I study “donor governance,” which occurs when contributors to non-profit firms place restrictions
on their gifts to limit the discretion of managers. In a study of U.S. art museums, I find that this
practice has grown significantly in recent years, and it represents the largest source of permanent
capital in the industry. When donor restrictions are strong, museums shift their cost structures
away from administration and toward program services, and they exhibit very high savings rates,
retaining in their endowments 45 cents of each incremental dollar donated. Retention rates are
near zero for cash generated from other activities. Restricted donations appear to stabilize nonprofits and significantly influence their activities, but they reduce management flexibility and
may contribute to lower profit margins. Rising donor governance in U.S. art museums may
represent a reaction by contributors to the industry’s high rates of financial distress, weak boards
of trustees, and large private benefits of control enjoyed by managers.
I am grateful to Tumi Adebiyi and Siddharth Vij for excellent research assistance, and I thank Jianping Mei, Michael
Moses, and Ashley Newton for graciously sharing their data with me. I appreciate helpful comments from Tumi Adebiyi,
David Lesmond, Ashley Newton, Michael O’Hare, John Page, Johann Reindl, Gudrun Rolle, Siddharth Vij, Leonard
Wolk, seminar participants at the University of Adelaide, Baruch College, BI Norwegian Business School, University of
Edinburgh, Erasmus University Rotterdam, Free University of Amsterdam, IESEG Paris, Melbourne University, Tulane
University, the University of Western Australia, and students in my NYU doctoral seminar on corporate distress and
restructuring. Part of this paper was completed while I was a visiting professor at Erasmus University Rotterdam.
Donor Governance and Financial Management
in Prominent U.S. Art Museums
I.
Introduction
This paper studies the role of restricted donations in financing major U.S. art museums.
Charitable gifts play a critical role in supporting museums and other non-profit corporations, and
accumulated restricted donations represent a significant and growing amount of the capital
invested in the museum industry. When donors place restrictions on these contributions, the
funds resemble equity investments with restrictive covenants, a source of financing unknown in
the for-profit sector. Restricted donations permit benefactors to influence a non-profit
organization for decades, even after the donors may have severed all connections or died. While
restricted gifts provide stability and probably encourage a greater rate of contributions, they also
limit operating flexibility in a way that could compromise an organization’s efficiency.
Restricted donations represent a form of corporate governance, because they constrain the
opportunities for non-profit managers to expropriate resources. I call this practice “donor
governance.” The rationale for this type of donor control increases when other forms of
governance are weak and information asymmetry between donors and managers is high. These
conditions seem to characterize art museums, which have oversized, ceremonial boards of
trustees and are managed by professional curators with specialized education from elite
universities. For the curatorial staff, art museums offer potentially large private benefits of
1
control, since their positions provide exquisite working conditions and offer entree into the high
society of museum patrons and donors.
Although a minority of U.S. art museums have implicit financial protection due to
government or university ownership, the vast majority are public charities overseen by selfperpetuating boards of trustees, and I focus my analysis on these independent museums. These
organizations raise their own financial resources, make decisions about balance sheet leverage
and undertake long-term capital investments. The potential agency problems in these art
museums provide an interesting reason for examining their financial structure, and a further
rationale comes from museums’ recurring encounters with financial distress.
While museums enjoy a variety of government subsidies such as tax deductible
donations, discounted utilities, and millage taxes, they remain exposed to considerable market
risk, and sometimes things go very wrong. Art museums’ financial problems seem more than
ironic, because many of them rank among the very wealthiest businesses in the economy, with
vast collections of sought-after assets that appreciate in value and draw crowds of paying
customers.1 Among many recent examples of museums facing financial crises, the Los Angeles
Museum of Contemporary Art experienced a massive restructuring between 2008-13 that
included a failed merger attempt with a cross-town competitor; the New York based American
Folk Art Museum defaulted on a bond issue in 2011 and vacated its headquarters for a far smaller
location; and the Detroit Institute of Art became ensnared in that city’s 2013 bankruptcy when
1
A former assistant curator at the Metropolitan Museum of Art in New York estimated its collection’s fair
market value at more than $100 billion in 2008, as recounted in Gross (2009). O’Hare (2015) reports an estimate of $26
billion to $43 billion for the collection of the Art Institute of Chicago.
2
Detroit’s creditors pursued the museum’s art collection to satisfy the municipality’s debts. 2
Studying a panel dataset of prominent U.S. art museums between 1999 and 2013, I find
that donor governance in the form of restricted donations has greatly increased in recent years
and significantly impacts museums’ balance sheets and cost structures, in ways that both help
and hurt their overall financial performance. Museums with high amounts of restricted donor
capital tend to spend more on programming and less on administration, which suggests that
donors successfully limit the appropriation of resources by management. These museums also
exhibit more stability in year-to-year operating margins. However, their margins are lower
compared to museums who receive gifts with fewer restrictions, implying that the loss of
operating flexibility that accompanies donor governance can be costly.
Figure 1 shows the total capital reported on the balance sheets of the 129 major art
museums that form the sample for this study, as described more fully below. The figure shows
an unmistakable trend over the 1999-2012 period of a reduction in unrestricted assets in favor of
assets whose uses are temporarily or permanently restricted. More debt has also entered
museum’s capital structures at the same time. As a result, museums have far less financial
flexibility and operating discretion than before. The figure also shows clearly that restricted
donations are the most important source of permanent capital in the art museum industry, even
though widely recognized ethical guidelines state that museums should seek unrestricted gifts
2
Detroit’s flagship art museum was founded by the city in 1885 but spun off decades ago into a self-governing
independent entity. However, the city retained title to the art collection in order to improve its position as a borrower in
the municipal bond markets. The collection was appraised as high as $8 billion during the bankruptcy proceedings before
a negotiated settlement extricated the art from the case. As discussed below, a handful of other museums have similar
situations, with their art collections wholly or partly owned by the municipalities where they are located.
3
“whenever possible.”3 The figure is also misleading, because museums do not capitalize the
value of their collections as assets on their balance sheets; when a museum purchases artworks
for cash, the cost is expensed immediately rather than capitalized, and when art is donated (the
much more common method of acquisition), no value is added to the organization’s balance
sheet even though appraisals are often procured by donors to justify personal income tax
deductions. Donated art can be subject to restrictions just like cash contributions, so it is unclear
whether including the fair market value of a museum’s collection as a balance sheet asset would
alter the message conveyed by Figure 1 of donor restrictions increasing dramatically over time.
Certain costs and benefits of restricted donations can be observed by studying the inflows
and outflows of funds from museums’ endowment funds. A recent expansion in disclosure
requirements permits me to examine a four-year history of savings and spending from museums’
endowments. Analyzing the sensitivities between various revenue sources and changes in the
organizations’ endowments, I find that museums add about 45 cents of each donated dollar to
their endowments, an extraordinarily high savings rate that must surely occur as a byproduct of
donor restrictions, which may affect the rate of spending either directly (by imposing time
restrictions) or indirectly (by stipulating a restrictive set of uses for the curator). In contrast,
museums’ endowment savings rates for operating surpluses and other sources of cash are
virtually zero. When faced with operating shortfalls, museums draw down their endowments to
cover operating deficits, but only at a lower rate of 13 cents per dollar decline in income, which
3
Principle 17 of the Professional Practices in Art Museums promulgated by the Association of Art Museum
Directors states that “Gifts and bequests should be unrestricted whenever possible. No work of art should be accepted or
acquired with conditions that restrict or otherwise interfere with the museum’s obligation to apply the most reliable
scholarly and scientific information available to questions of attribution, dating, iconography, provenance, conservation,
and related matters.” See https://aamd.org/sites/default/files/document/2011ProfessionalPracitiesinArtMuseums.pdf.
4
is likely also limited by donor restrictions on the uses of prior gifts. Museums’ constraints
against using endowment funds as a buffer against operating losses force managers to make
difficult choices about reducing operations when business turns down, which is likely the
intention of their donors. Related restrictions against the “deaccessioning” or sale of artwork,
discussed in more detail below, play a similar role in forcing museum curators to balance their
budgets.
Art museums offer an interesting opportunity to test Merton’s (1993) hypothesis that nonprofits should invest their endowments to hedge the value of other assets they own. Testing this
hypothesis is difficult when studying non-profit organizations such as universities, but museums
offer a much cleaner setting since their principal assets, fine art, comprise an investable asset
class whose rates of return have historically provided a hedge against the returns on stocks,
bonds, and other securities held in endowments, as shown by Mei and Moses (2002). However, I
find no significant evidence that museums take account of rates of return in the art market when
investing their financial endowments.
This research extends our knowledge of the governance of major non-profit institutions,
which dominate important, highly visible industries in the U.S. economy including the arts,
education, healthcare, and religion. My focus on donor governance identifies a channel for
control of non-profits and complements other recent papers on aspects of non-profit governance.
For example, Newton (2015) shows the importance of effective board oversight for impacting
operating results in the non-profit sector, while Hallock (2002) and Eldenburg et al. (2004)
illustrate the role of executive incentives and the threat of dismissal in motivating non-profit
managers to perform.
5
The remainder of this paper is organized as follows. Section II discusses the organization
and economics of the art museum industry in the U.S. Section III describes the data set used in
this study and presents descriptive statistics about restricted donations and other aspects of
museums’ financing. Section IV contains the main analysis of museums’ endowment funds, cost
structures, and financial performance. Section V concludes the paper.
II.
Organization and Economics of Major U.S. Art Museums
Most museums have a timeless mission, exhibiting fine art masterpieces for public
viewing in a format that has not changed in centuries. Because of the iconic nature of their
collections, leading museums are relatively invulnerable to shifts in tastes or consumer
technology, and they can rely on a more or less permanent clientele of visitors. Therefore, the
economics of the industry are quite stable, as described in papers on the creation and early history
of U.S. art museums by Smolensky (1986) and Temin (1991). On the cost side, museums have
extreme operating leverage, with nearly all of their costs fixed except in the very long run. The
marginal cost of accommodating an additional visitor is almost zero, and museums use a variety
of strategies such as a heavy reliance on volunteer docents in order to align their operations with
short-term changes in visitor demand. Frey and Meier (2006) provide a detailed survey of the
sizeable number of published papers studying various aspects of museums’ business operations.
Museums obtain most of their revenue from donations, with a minority coming from
admission charges, membership subscriptions, and other user fees. In recent years, for-profit
affiliated operations such as restaurants and gift shops have also subsidized some museums’
operations, especially in larger cities with high tourist traffic. While some donors make
6
unrestricted gifts to support all aspects of museum operations, Temin (1991) describes the
longstanding preference of donors to restrict gifts for expansion of facilities, acquisitions of new
art, or preservation of a museum’s collection. 4 Donations are tied to cycles in the economy and
can vary considerably from year to year due to fluctuations in the stock market, as shown by
Blanchett (2014). However, museum attendance tends to behave counter-cyclically according to
Skinner, Ekelund and Jackson (2009), which should somewhat offset the instability of the
donation stream (I find no evidence of such a pattern in my sample). Additions of art objects to
museum collections usually occur as bequests whose timing is almost entirely idiosyncratic.
Although a buoyant collectors’ market exists for the buying and selling of art
masterpieces, museums do not participate in this market on a large scale. Total 2012 spending
on art acquisitions by all 129 museums in my sample was just $256 million, about 80 percent of
it by the top 10 museums. In contrast, the size of the worldwide art market is about $60 billion
per year.5 Museum sales of art from their collections are severely constrained by codes of ethics
that generally prohibit the deaccessioning of museum pieces except under very narrow
circumstances.6 In principle, the ability to sell off surplus art could serve as a safety valve to
4
Many types of restrictions appear in charitable gifts, such as requiring an institution to use the funds to
construct a building, to pay the salary for a particular position, or to award a traveling fellowship to a researcher in a
specific field. Over time, purposes of a gift can become obsolete or peripheral to the mission of an organization, and both
private and public lawsuits occasionally occur to enforce gift restrictions or permit their relaxation. Opposing views of
the merits of donor restrictions, as well as abundant examples, appear in Feld, O’Hare and Schuster (1983) and Lotkin
(1999). A good account of recent art museum controversies over donor restrictions can be found at
http://www.nytimes.com/2013/02/05/arts/design/museums-grapple-with-onerous-restrictions-on-donations.html.
5
See http://www.artnet.com/magazineus/news/artnetnews/china-the-worlds-top-art-and-antique-market.asp.
6
In one prominent recent example, the Albright-Knox Art Gallery in Buffalo, NY, in 2007 raised $28.6 million
by auctioning a bronze sculpture from its collection. It complied with standard ethical guidelines by earmarking the
proceeds for an acquisitions endowment fund, essentially exchanging one piece of art for the resources with which to
purchase others and rebalance the span of the overall collection. However, the transaction caused considerable
controversy in the city and in the museum industry.
7
generate revenue when museums’ other funding dries up, but to the extent that these sales of art
actually occur, museums use extreme discretion to avoid negative publicity. For example, some
museums evade the restrictions against deaccessioning by immediately selling newly donated art
without ever formally accepting it into their collections, and others have reportedly scrubbed
evidence of prior ownership from historical records when selling off pieces of art.
Temin (1991) explains that donor restrictions on gifts and the ethical rules against
deaccessioning arose as forms of bonding between donors and a museum’s trained curators, who
achieved operational control of most museums in the first part of the 20 th century. These
restrictions prevented the museum’s professional staff from consuming the value of its
collections through excessive compensation or fringe benefits. Numerous other contractual
restrictions, such as governments’ limits on the use of tax-exempt bond proceeds that museums
are permitted to issue, play a similar role in limiting agency costs. However, constraining
managers’ perquisite consumption represents a chronic governance issue for museums, because
the private benefits of control enjoyed by museum directors can be large. Some museum
directors live rent-free on the premises, which are often located in the most desirable districts of
cities, and international travel for research or consultation with the staff of other museums occurs
frequently. The work environment for managers of museums is sublime, with careful climate
control, high security, great attention to order and cleanliness, and, of course, exquisite decor.
Curators also exercise power as social gatekeepers for rich donors, who seek entry to an elite
network that receives invitations to private museum receptions, gallery openings, and fundraising
luncheons.
Fama and Jensen’s (1983) landmark work on organizational design recognizes the
8
inherent risk of agency problems in non-profit enterprises, since unlike other organizations, nonprofits have no residual claimants who would have incentives to monitor the professional staff.
As predicted by Fama and Jensen, museum governance is overseen by independent boards of
directors that are typically comprised exclusively of outsiders, many of them current or
prospective donors. However, most museum boards are too oversized to operate effectively
(Aggarwal, Evans, and Nanda, 2012), with a mean of 32.6 directors in my sample. Therefore,
they tend to play ceremonial roles with considerable free-riding. Actual monitoring
responsibility, to the extent it is exercised at all, is generally delegated to various subcommittees
such as an executive committee or an audit committee. Until recently, the lack of public
disclosure about the composition and qualification of non-profit boards limited the scope of
academic research into their effectiveness. Capitalizing on new data provided by a major 2008
disclosure reform, Newton (2015) uses 16 variables to create a governance index for non-profits,
finding that better governed organizations succeed in constraining the compensation and benefits
of managers, leading to better operating performance. The leading prior paper studying art
museum governance is Oster and Goetzmann (2003), which examines variables such as the date
of a museum’s founding and whether its ownership structure is government, private, or
academic. The authors find that a museum’s choice of mission depends on its ownership
structure, among other variables.
Donor restrictions, the focus of this study, represent a channel of governance that has
received relatively little attention in academic studies. In the finance literature, Mensah and
Werner (2003) study a sample of universities and find that cost efficiency declines when more of
the organization’s net assets are unrestricted. Li, McDowell, and Hu (2012) find that an
9
organization’s intake of new donations increases when it permits donors to place restrictions
upon the use of their gifts. In accounting research, Yetman and Yetman (2012) and Ling and
Roberts (2014) have found improvements in the quality of financial reporting when a larger
fraction of an organization’s reserves are restricted, suggesting that major donors act as effective
monitors and demand better disclosure. Wolk (2014) is the most ambitious study of donor
restrictions to date, using a large panel dataset of thousands of United Kingdom charities between
2007-2011. In a wide-ranging investigation, the author finds that donor restrictions appear to
hurt the profitability of low-performing charities but have the opposite effect on well-performing
ones. The results of Wolk’s research are not directly comparable to the investigation of art
museums that I undertake in this paper, partly because the presentation of data differs in
significant ways for U.S. and U.K. non-profits, and also because the typical charity in his allindustry sample is much smaller (less than £1 million in assets) and has vastly more unrestricted
funds (a median of 91.7 percent) than the 129 top-shelf art museums in my sample, for which the
median values are $47 million of total assets and 52.0 percent of unrestricted funds.
III.
Sample Selection and Data Description
The sample for this paper is drawn from the 242 museums that belong to the Association
of Art Museum Directors (AAMD), an organization founded in 1916 to establish professional
standards and advocate for the interests of the museum industry in the United States. Virtually
every culturally significant fine arts institution in the U.S. belongs to the AAMD, including a
handful that do not have permanent collections because they operate as fine arts academies or
host only traveling exhibitions. I exclude these non-collecting institutions and also drop
10
museums that are owned by or affiliated with universities, and museums that are entities of
federal, state, or municipal government. For many of these excluded museums, separate
financial disclosures are not available, and for all of them the issues of financial risk are
fundamentally different than those faced by the independent museums that I analyze below.
These exclusions narrow the sample to 136 museums, and I must exclude a further seven because
they are legally organized as private foundations rather than public charitable trusts. 7 Private
foundations file an abbreviated Form 990-PF rather than the more complete Form 990 with the
U.S. Internal Revenue Service, so that the financial data required for the analysis below is
generally not available for them.
I obtain a final sample of 129 museums, including nearly every well-known independent
museum in the U.S. such as the Metropolitan Museum of Art in New York, the Museum of Fine
Arts in Boston, the Art Institute of Chicago, and so forth. I use the database of Guidestar.org to
obtain Form 990 financial data for the 129 museums in the sample, and for most institutions I
have 14 annual observations for the period 1999-2013 and up to 1,789 museum-year
observations for the sample overall. Missing values in the dataset are typically caused when
museums do not complete all the required fields in the Form 990.
Table 1 presents summary statistics for basic financial information for the museums in
the sample. The data indicate that museums are largely financed by donations, which I define as
the sum of charitable contributions plus government grants. The mean value of donations per
museum-year is about four times larger than the mean value of program service revenue, which is
7
Unfortunately the small group of excluded private foundation museums includes two of the best capitalized,
the Getty Museum in Los Angeles, CA, and the Crystal Bridges Museum of American Art in Bentonville, AR.
11
comprised of admission charges, memberships, and related fees paid by the customers of a
museum. The disparity between contributions and user fee income would be much greater if the
value of donations of artwork were included, but under accounting rules such gifts typically do
not appear on museums’ financial statements due to the difficulty of determining their fair
market value. In addition, the relationship between donations and program service revenue is
completely different for art museums compared to the overall U.S. non-profit sector. Aggregate
statistics indicate that 73% of all non-profit revenue came from program services in 2012, with
21% obtained from donations, almost the mirror image of the composition of revenue for art
museums.8 Data in Table 1 also suggest the difficulty faced by museums in balancing their
budgets, as the mean value of total expenses exceeds the sum total of the mean values of revenue
from donations and program services. The difference must be made up from investment income
and drawing down financial reserves.
The asset base of museums as shown on their balance sheets is comprised mostly of
financial investments, which are usually held in endowment funds. Almost half of the assets of a
museum are restricted by donors, in the sub categories of temporarily restricted (21% of total
assets, on average) and permanently restricted (26% of total assets, on average). The distinction
between the two categories arises over whether a donor’s condition is perpetual or expires after a
finite period.
During the 1999-2013 sample period, museums appear to have embarked on a borrowing
and building spree. The average leverage of a museum in the sample, calculated as total
liabilities over total assets, rose during this period from about 8% to 15% of total assets, while
8
See http://nccs.urban.org/statistics/quickfacts.cfm.
12
fixed assets as a fraction of total assets rose by about a third, from 24% to 32%. During this time
the number of museums with tax-exempt bonds outstanding to public investors increased from
13 to 36. Figure 1 provides insight into the time trend of museums’ capital structures during the
sample period. The figure shows the aggregate capital invested in the 129 museums in the
sample, with the sum of each category divided by the sum of total assets for the industry as a
whole. In addition to the steady increase in debt finance, the amount of permanently restricted
and temporarily restricted assets has grown as well, increasing far faster than unrestricted assets.
Unrestricted assets available to management have declined by about one-third, from about 45%
of capital in 1999 to about 30% in 2013. If restricted assets are considered a form of pseudodebt, since they cannot be used for general obligations of the organization, then museums are
extremely leveraged.
Issuing risky debt makes museums’ art collections vulnerable to foreclosure in the event
that the organization cannot make its payments and defaults, although placing the art into a trust
fund protected from creditors can circumvent this risk. In my sample, only four museums out of
129 appear to have taken this step, based on disclosures in their loan documents, and only one of
these four currently has bonds outstanding.9 In six cases, museum collections appear to be at risk
to the finances of their host city, as the municipality retains title to all or part of the collection,
which could potentially be seized by city creditors in the event of a bankruptcy filing such as
Detroit’s.
9
A number of museums appear to rely implicitly for protection from creditors upon the concept of a cultural
trust, which asserts that creditors cannot seize assets that are held for the benefit of the public. See Tam (2012). This
position was taken by the attorney general of the state of Michigan during the bankruptcy of Detroit. The U.S.
bankruptcy judge did not appear to agree with this doctrine, as he oversaw a negotiated settlement in which donors to the
Detroit Institute of Arts and the museum itself agreed to pay hundreds of millions of dollars to the city’s creditors in order
to remove any encumbrance upon the museum’s collections.
13
Perhaps the most surprising omission in museums’ risk management policies is the nearuniversal choice not to insure their collections against theft or casualty loss. The total spent on
insurance for all the museums in the sample in 2012 was just $33.2 million, far less than the cost
of one top-shelf painting in today’s art auction market. According to a recent report by a national
magazine, the worldwide market for fine art insurance is somewhere between $500 million and
$1 billion in premiums per year, meaning that “there’s a lot of uninsured art out there.” 10 A
number of recent famous art thefts, such as the 1990 heist of a Rembrandt and other pieces from
the Isabella Stewart Gardner Museum in Boston, MA, have been followed by revelations that the
pieces were not insured. Nicita and Rizzolli (2009) argue that the failure of museums to carry
insurance represents a strategic decision, rather than an example of reckless risk management.
According to their argument, the availability of insurance could tempt art thieves into stealing
paintings to extract ransom from the insurer, so that not carrying insurance represents a
commitment device whereby museums credibly pledge not to negotiate with thieves. A similar
argument by these authors rationalizes the light security in place at most museums not as a costsaving strategy, but rather as an attempt to avoid calling attention to the value of the art.
Table 2 presents data about the growth rate and riskiness of various museum revenue
streams during my sample period. While overall museum revenue rose at a modest rate of 2.0%
per year, the striking data appear in the third column, which shows the standard deviation of the
annual growth rates in each sub-category of revenue. With the exception of endowment
investment returns, each of the four major revenue streams of program services, donations,
government grants, and other revenue are subject to large year-to-year swings in growth rates,
10
See http://www.forbes.com/sites/kathryntully/2012/10/31/should-your-art-be-insured/.
14
much larger than the estimates for arts organizations reported by Blanchett (2014). For example,
the standard deviation of the growth rate in donations is about 70% per year, so that a museum’s
use of its brand as the basis of a fundraising franchise yields returns that are about two to three
times more volatile than a typical publicly traded stock. A correlation matrix on the right side of
Table 2 shows that these revenue streams exhibit almost zero association with one another,
suggesting that museums must compartmentalize the management of fundraising, exhibits, grant
writing, and ancillary business units and hope that not all of them go bad at the same time.
Museums’ vulnerability to financial and other risks may occur as a strategic choice or as a
consequence of market incompleteness. For instance, the market for art insurance may be too
small or prohibitively expensive for museums to cover their masterpieces. Or museums may
self-insure because they have an overabundance of art, far too much to display, so that if a work
is damaged or stolen, it can be replaced with one held in inventory. Museums may wish to seem
vulnerable in order to attract benefactors or to position themselves for government bailouts or
subsidies. These hypotheses seem intriguing, but data necessary to test them is not readily
available.
IV
Analysis
This section analyzes the impact of donor restrictions upon museums’ financial policies
and performance. I begin by examining when museums contribute to and withdraw funds from
their endowments in regression analysis shown in the first three columns of Table 3.
For non-profit corporations, endowment funds provide a form of risk reduction since they
contain reserves that can cover the organization’s debts. If the endowment is large enough, it can
15
provide an income stream enabling the organization to rely less on user fees and donations.
While a fairly large literature such as Lerner, Schoar, and Wang (2008) has studied the
investment performance and asset allocation of endowment funds, far fewer papers have
examined the conditions under which non-profits add to or withdraw capital from them. Most of
the literature on this topic, such as Brown, Dimmock, Kang, and Weisbenner (2012) and Cejnek,
Franz, Randall and Stoughton (2013), uses self-reported survey data,11 and to my knowledge this
paper is the first to analyze organizations’ disclosures of annual endowment inflows and outflows
as reported in Schedule D, Part V of Form 990. Out of the 129 museums in the sample, 120
report endowment data on this section of the form, most of them beginning in the year 2008
when these disclosures were first required. Descriptive statistics about endowment sizes,
contributions, distribution rates, and investment returns appear in the lower half of Table 1.
The first three columns of Table 3 show the incremental effect upon endowment
contributions and withdrawals of increases in different sources of cash, in a framework
analogous to the “cash flow sensitivity of cash” studied by Almeida, Campello and Weisbach
(2004). The analysis takes advantage of the financial reporting rules that require non-profits to
disaggregate their revenue streams into programming, gifts, grants, and ancillary sources, a
decomposition that provides insight that is generally not available when analyzing the net sales
revenue of publicly traded firms. The table presents estimates from least squares regressions
with the dollar value of endowment contributions as the dependent variable in the first column,
11
Nearly all prior endowment research uses survey data from the higher education industry compiled by the
National Association of College and University Business Officers (NACUBO). While the completeness of this data has
improved over time, it has been subject to survey self-selection effects, changing variable definitions, and a reliance on
self-reporting by those universities that cooperate. A comprehensive evaluation of the NACUBO data’s quality appears
in Brown, Garlappi, and Tiu (2010).
16
the dollar value of endowment withdrawals as the dependent variable in the second column, and
the net of contributions minus withdrawals in the third column. The main explanatory variables
are the dollar value of cash donations received, the operating surplus of program service revenue
less program service expense, the dollar value of earnings within the endowment itself, the dollar
value of new debt issued in the form of loans, notes, or bonds, the dollar value of government
grants received, and the dollar value of cash on the balance sheet at the start of the fiscal year.
All models include fixed effects for museums and for individual fiscal years, since the market
investment climate will obviously affect decisions about how to manage the endowment.
The most striking result in Table 3 appears in the top left cell, which shows that for each
dollar in gifts received, 45 cents is typically added to a museum’s endowment. This is an
extremely large savings rate, and it appears even more surprising when compared to the
coefficient on operating profits in the cell immediately below. That estimate is virtually zero,
implying that museums save almost half of their donations but none of their profits. Since
money is fungible, it is not clear why these coefficients should differ so markedly, if at all, and it
seems likely that the explanation comes from donor restrictions forcing museums to save gifts
and spend them gradually over time. A related alternative explanation is that many gifts are
solicited for the express purpose of building an organization’s endowment fund. Unfortunately
little research exists into the frequency, scale, and use of proceeds of non-profit firms’ capital
campaigns, which appear to play a role quite similar to rights issues by public corporations.
The first column of Table 3 also shows a strongly negative relation between new grant
income received and endowment contributions. Intuitively, an increase in cash from grants
should free up other resources and perhaps cause an increase in endowment contributions. The
17
negative association likely occurs because government grants often require organizations to raise
or provide a matching amount of money to support the project being funded.
I do not find a significant association between new debt issues and increases in
endowment funds. This provides evidence against the hypothesis of “endowment arbitrage,”
which conjectures that wealthy non-profits issue debt at low interest rates, often due to income
tax subsidies for the lenders, and then invest the proceeds to earn a higher return in the stock
market via their endowments. See Congressional Budget Office (2010) for a study of this
endowment arbitrage pattern in the higher education industry.
The second column of Table 3, studying endowment withdrawals, contains one notable
result, a negative estimate of -0.13 for the variable measuring operating profits. The estimate
implies that when a deficit occurs in museum operations, only a fraction is covered by funds
taken from the endowment.
The third column of the table consolidates the results shown in the first two columns and
shows the impact of different changes in cash upon the net inflow of funds to or from an
endowment. In principle, the coefficients on the six variables should not vary greatly from one
another due to the fungibility of cash, but the analysis confirms the result that museums save a
very large proportion of their gifts, a modest (though insignificant) fraction of their operating
surpluses, and reduce the endowment to support projects that are funded by government grants.
The coefficient on the donations variable is far larger than any of the other effects, suggesting the
large influence of donor governance.
I find little evidence in Table 3 that the performance of the endowment fund itself affects
additions by or distributions to the organization. Estimates for the variable measuring annual
18
endowment performance are virtually zero and not significant, except for a marginal result of
small magnitude in the first column. These findings are not consistent with Brown et al. (2012),
who find that university endowments reduce payout rates following negative investment shocks,
but do not raise them following positive shocks, consistent with a hoarding or accumulation
management strategy.
In the right two columns of Table 3, I study the impact of various sources of cash flow
upon museums’ cash balances and their investments in fixed assets, akin to property, plant and
equipment. Estimates in the top row indicate that about 14 cents of every dollar donated is held
on the balance sheet as cash, while 11 cents per dollar of donations is spent on increasing the size
of the museum facility. Strikingly, when museums earn operating profits, about 50 cents per
dollar is spent on new bricks-and-mortar expansions of the museum.
Table 4 investigates the impact of donor restrictions upon the investment performance of
museums’ endowments. The main hypothesis is that restrictions reduce the expected investment
return, since assets earmarked for a specific use might be invested either in cash or risk-free
bonds. The first column of the table provides a benchmark, showing the results from a standard
Fama-French four factor model in which the annual endowment return is regressed against the
excess return on the stock market as well as the factors for growth stocks, small stocks, and
momentum. Standard errors are clustered by museum within the sample of 490 annual
observations. The key estimate in the table is the coefficient of 0.52 on the market return, a
relatively low value suggesting that museum endowments are conservatively managed with close
to half of their assets earning the risk-free rate.
I introduce the Mei-Moses art index as an additional risk factor in the middle column.
19
Based on the research methods described in Mei and Moses (2002), this index uses auction data
to track the semi-annual performance of the art market as an alternative investment asset class.
For the minority of museums whose reporting periods do not end in June or December, I take a
weighted average of the returns on the Mei-Moses index during the months contained in each
fiscal year. According to Merton’s (1993) theory paper on endowment management, an
organization should invest its endowment in assets whose returns are uncorrelated or negatively
correlated with changes in the values of the organization’s own assets. An alternative hypothesis
cuts in the other direction: if endowment assets are held partly to finance future purchases of fine
art, one might over-weight the portfolio with securities that exhibit a positive correlation, rather
than a negative one, with the market values of art on the open market.
Testing whether endowment funds are used to hedge the value of an organization’s other
assets is difficult for most non-profits given the breadth of their asset bases, 12 but art museums
are an exception, since most of their wealth is held in fine art, and the appreciation of the art
should track indexes of art market investment returns. I find inconclusive evidence that any such
hedging occurs in museum endowments. When the Mei-Moses index is included as an
additional risk factor in the Fama-French model, it has an estimate of virtually zero, as shown in
the second column of Table 4. This indicates that the art market has no explanatory power for
the investment returns earned by art museums in their endowment funds; museums do not invest
in stocks that are correlated with art returns. This conclusion is basically unchanged if I drop the
stock market return from the model in the second column and use only the Mei-Moses index
12
The closest paper to running such a test appears to be Dimmock (2012), which establishes that the standard
deviation of endowment returns for a sample of universities is inverse to the standard deviation of the non-investment
revenue streams, so that the most stable universities tend to have the riskiest endowment investment policies and vice
versa.
20
instead; in that model, the index has an insignificant estimate of +0.04.
The third column of Table 4 tests whether endowment returns are lower due to more
conservative asset allocation by those museums that have high amounts of restricted assets. I
multiply the stock market index by the ratio of restricted assets over net assets; this quotient
represents the fraction of a museum’s assets, excluding those financed by debt, that are
encumbered by donor restrictions. My hypothesis is that this interaction term should have a
negative sign, reducing the overall portfolio association with the stock market, if restricted assets
are invested conservatively. However, as shown by the positive and significant estimate of
+0.036, this hypothesis is not supported by the data. While it continues to appear that museums
manage their endowments conservatively, this conclusion does not strengthen based upon the
presence of donor restrictions.
I study the impact of donor restrictions upon museums’ operations in Tables 5 and 6. The
first analysis in Table 5 uses regression analysis in a panel data setting to study three dependent
variables: the ratios of administrative expenses over total expenses, program service expenses
over total expenses, and fundraising expenses over total expenses. Independent variables include
the ratios of temporarily restricted assets over total assets and permanently restricted assets over
total assets. Other control variables include the size of the museum, measured as the log of
program service revenue, fixed asset intensity, leverage, and fixed effects for individual
museums and fiscal year periods.
Estimates for the coefficient of permanently restricted assets indicate that donor
restrictions impart large and significant impact upon museums’ cost structures. Estimates for this
variable in the first two columns indicate a shift of the cost structure, taking resources out of
21
administration and placing them into programming when donor restrictions are high. The
interpretation is that these museums spend less on administrative overhead and more on
exhibitions and other programming directly in line with their missions, surely a goal that most
donors would share. The costs of managerial compensation and various private benefits, while
not transparently shown in the financial statements, would appear in various sub-categories of
administration, so donor restrictions appear to be successful in reducing curators’ private benefits
of control. For the variable measuring temporarily restricted asset intensity, the two models have
coefficient estimates with the expected signs, but they are smaller in magnitude compared to
those for permanently restricted assets and are not statistically significant.
The results reported in Table 5 are probably the most important in this study, although
they would also be consistent with an alternative hypothesis that firms manipulate their financial
accounting by reclassifying expenses from one category to another when donors impose spending
restrictions. Even if the results occur as a result of the more benign hypothesis, that donor
governance imposes a strong influence upon museums’ spending priorities, they do not
illuminate whether donor restrictions improve the overall efficiency of a museum. I study that
question in Table 6, where I look at the level and volatility of a museum’s profitability in
regression analysis identical to that used in Table 5. The first two columns of Table 6 have
measures of return on assets as the dependent variables. In the first column, the “museum ROA”
variable equals all non-investment revenue, minus non-investment expense, divided by the book
value of assets that are not listed as investment securities or other investments. In the second
column, the “investment ROA” equals the net change in investment assets during the year
divided by investment securities plus other investments at the start of the year. In the third and
22
fourth columns, I use the squared values of these two variables as the dependent variables, in
order to study whether the riskiness of an organization’s performance has a significant relation to
donor governance via restricted gifts.
As in Table 5, the permanently restricted gift ratio has a strong and significant estimate in
all four columns of Table 6, while the temporarily restricted gift ratio has insignificant and
generally smaller estimates. Firms with fractions of permanently restricted assets exhibit lower
operating performance, though the result is not statistically significant, and sharply, significantly
lower investment performance. This result is inconsistent with the findings in the right column
of Table 4, but the analysis in that table was based only on assets designated as part of museum
endowments. Some restricted assets may be held outside the endowment portfolio, in the form
of cash or time deposits that the organization treats as an investment for reporting purposes. If
these accounts earned little or no interest it would be consistent with the finding of lower
investment returns in Table 6.
Finally, estimates in the right two columns indicate that museums exhibit significantly
less volatile operating and financial returns when their restricted gift ratios are high. This seems
to be an important result, given the risk management problems of many museums that are
documented above. In addition to affecting museums’ cost structures, donor restrictions appear
to push museums toward more financial stability, albeit at a cost of less flexibility that may
undermine profitability.
V.
Conclusions
This paper studies the role of donor governance, which takes the form of restrictions
23
placed upon charitable gifts to non-profit corporations. For an organization, receiving a donation
with strings attached is analogous to an increase in permanent equity capital with restrictive
covenants that are more commonly associated with debt capital. Evidence from a panel data set
of leading U.S. art museums indicates that when donors place restrictions upon the use of new
capital, these constraints appear to reduce agency problems by shifting the museum’s spending
away from administration and into programming. This redistribution of costs might reduce
agency costs by limiting perquisite consumption and asset substitution, among other problems. I
find that museums have less variable performance when they receive large amounts of
permanently restricted gifts, and this result seems closely associated with an additional finding,
that a large fraction of incoming gifts are placed into museums’ endowments. However, these
financial benefits come at the cost of reduced operating flexibility, and as a result museums’
profit margins are lower when restricted gifts are sizeable.
Donor governance represents an important channel through which the financial backers of
nonprofit firms influence the behavior of management, but we know relatively little about its
details. For instance, what types of restrictions are used in practice? What is their typical
duration? How successfully do managers limit or contract around them? Does any competition
among potential contributors enable the firm to raise donations with reduced restrictions, just as
firms sometimes succeed in issuing “covenant lite” debt? Future research into these and other
questions has the potential to illuminate our understanding of what may be the most significant
source of capital for the non-profit sector.
24
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27
Table 1
Descriptive statistics
The table shows descriptive statistics for financial data for a sample of 129 U.S. art museums between 1999 and 2013. The lower part
of the table shows data for a subsample of 120 museums for which endowment data is available between 2008 and 2013. Leverage
equals total liabilities over total assets. Days payables is calculated based on program service expense. The endowment spending rate
equals distributions divided by the value of the endowment at the start of the year. The endowment investment return equals
endowment earnings divided by the sum of the value of the endowment at the start of the year plus one-half the value of endowment
additions during the year. All dollar values are in millions. All balance sheet data is recorded at the start of the year. Data are
obtained from museums’ U.S. Internal Revenue Service Form 990 filings.
Variable
Total assets
Leverage
Days payables
Program service revenue
Cash donations + Government grants
Program service expense
Total expense
Cash and equivalents / total assets
Temporarily restricted assets / total assets
Permanently restricted assets / total assets
Fixed assets / total assets
Endowment assets
Endowment additions
Endowment spending
Endowment spending rate
Endowment investment return
Obs.
1,769
1,763
1,765
1,764
1,762
1,768
1,789
1,763
1,763
1,763
1,758
Mean
149.1
0.13
64
3.6
14.5
15.2
19.6
0.091
0.210
0.260
0.269
Median
47.0
0.06
44
0.7
5.3
4.4
6.8
0.043
0.144
0.236
0.239
Std.Dev.
331.6
0.18
70
12.5
28.2
34.2
40.5
0.140
0.204
0.221
0.214
Min.
0
0
0
0
0
0
0
-0.024
0
0
0
Max.
3,552.2
1.89
990
214.4
518.8
404.2
462.6
0.932
1.532
0.935
0.996
491
491
491
490
491
102.5
3.1
5.8
5.8%
3.1%
27.7
0.4
1.5
4.7%
2.0%
237.8
9.1
15.5
11.1%
13.1%
0.2
-2.5
-3.4
-10.0%
-33.3%
2,313.1
133.8
153.9
189.5%
55.0%
28
Table 2
Growth, volatility, and correlation of museums’ revenue sources
The table shows the annual growth rates, standard deviations of the growth rates, and correlations among different museum revenue
sources. Program service revenue includes admission charges, memberships, and related costs. Other museum revenue includes
parking, restaurants, and gift shops. The growth rate for endowment investment income equals the annual investment return on the
endowment fund. All growth rates are compounded continuously to reduce the importance of outliers. The sample includes 1,789
annual observations for 129 museums. Data are obtained from museums’ U.S. Internal Revenue Service Form 990 filings.
Correlation with
Obs.
Mean
growth
rate
Standard
deviation
Program
service
revenue
Other
museum
revenue
Cash
donations
Government
grants
Program service revenue
Other museum revenue
Cash donations
Government grants
Endowment investment income
1,561
1,355
1,610
1,309
491
4.7%
- 8.5%
3.4%
1.8%
2.3%
52.0%
104.3%
70.0%
99.0%
13.6%
0.01
-0.02
-0.03
-0.13
-0.01
0.03
0.32
0.01
0.07
0.02
Total revenue
1,596
2.0%
61.4%
29
Table 3
Additions and withdrawals from art museum endowments
The table shows fixed effects regression estimates of the amounts of cash contributed to and removed from art museum endowments,
as a function of six potential sources of cash for the museum. The operating surplus equals program service revenue minus program
service expenses. New debt issued equals the year-over-year difference in bonds, loans, and notes outstanding. Government grants
received equals cash from newly awarded grants minus changes in grants receivable. The analysis includes 490 observations for 120
museums during the 2008-12 period. Data are obtained from museums’ U.S. Internal Revenue Service Form 990 filings.
30
Dependent variable:
Endowment
additions
Endowment
distributions
Net additions to
endowment
Change in
cash balance
Change in
fixed assets
Cash donations
0.45 ***
(0.03)
-0.01
(0.02)
0.46 ***
(0.04)
0.14 ***
(0.02)
0.11 ***
(0.03)
Operating surplus
- 0.001
(0.07)
- 0.13 ***
(0.04)
0.14
(0.08)
0.10 **
(0.04)
0.50 ***
(0.08)
Endowment earnings
- 0.01 *
(0.006)
0.001
(0.004)
0.01
(0.01)
-0.003
(0.004)
-0.03 ***
(0.01)
Net change in long-term debt
- 0.02
(0.03)
- 0.04 ***
(0.02)
0.02
(0.03)
0.15 ***
(0.02)
0.15 ***
(0.03)
Government grants received
- 0.23 ***
(0.03)
0.01
(0.02)
- 0.24 ***
(0.04)
0.01
(0.02)
0.17 ***
(0.04)
0.03
(0.04)
0.06 **
(0.03)
- 0.03
(0.05)
-0.67 ***
(0.03)
0.50 ***
(0.05)
490
Yes
Yes
0.72
490
Yes
Yes
0.97
490
Yes
Yes
0.85
490
Yes
Yes
0.78
490
Yes
Yes
0.69
Cash on balance sheet, start of year
Museum-year observations
Museum fixed effects
Fiscal year fixed effects
R2
Standard errors appear in parentheses. Significant at 1% (***), 5% (**) and 10% (*) levels.
31
Table 4
Investment performance of art museum endowment funds
The table shows Fama-French four-factor estimates of the annual performance of art museum
endowment funds for a panel of 120 museums during the 2008-2012 period. Standard errors
clustered at the firm level appear in parentheses below each coefficient estimate. The Mei-Moses
(2002) index reflects changes in the market value of fine art as measured semi-annually in the
private auction market. Endowment data are obtained from museums’ U.S. Internal Revenue
Service Form 990 filings. Stock market data are obtained from Prof. Kenenth French’s website,
and value for the Mei-Moses index were kindly provided by Profs. Jianping Mei and Michael
Moses.
Dependent variable:
Endowment
return
Endowment
return
Endowment
return
Intercept
- 0.007 **
(0.003)
- 0.007*
(0.004)
- 0.007 *
(0.004)
Market excess return
0.520 ***
(0.030)
0.520 ***
(0.030)
0.503 ***
(0.030)
0.036 *
(0.019)
Market excess return
x (Restricted assets / net assets)
Mei-Moses index
0.002
(0.024)
0.001
(0.024)
Small - large excess return
0.092 *
(0.046)
0.093 *
(0.047)
0.096 **
(0.047)
High - low excess return
0.044
(0.036)
0.042
(0.038)
0.041
(0.038)
Up - down excess return
0.128 ***
(0.037)
0.122 **
(0.060)
0.119 **
(0.060)
490
0.76
490
0.76
490
0.76
Museum-year observations
R2
Standard errors appear in parentheses. Significant at 1% (***), 5% (**) and 10% (*) levels.
32
Table 5
Impact of asset restrictions on cost components
The table shows fixed effects regression estimates of the cost structure of art museums as a
function of asset composition and size. The sample includes 129 private U.S. art museums
between 1999-2013. Data are obtained from museums’ U.S. Internal Revenue Service Form 990
filings.
Dependent variable:
Administration
/ total exp.
Program
services
/ total exp.
Fundraising
/ total exp.
Temporarily restricted assets / total assets
- 0.026
(0.017)
0.009
(0.018)
0.005 ***
(0.002)
Permanently restricted assets / total assets
- 0.091 ***
(0.021)
0.085 ***
(0.022)
- 0.001
(0.002)
Museum size
(log of program service revenue)
- 0.012 ***
(0.004)
0.018 ***
(0.004)
- 0.0007 *
(0.0004)
Fixed assets / total assets
- 0.015
(0.018)
0.047 **
(0.019)
0.005 ***
(0.002)
Leverage
-0.003
(0.020)
-0.001
(0.021)
-0.001
(0.002)
1,705
Yes
Yes
0.51
1,705
Yes
Yes
0.56
1,705
Yes
Yes
0.20
Museum-year observations
Museum fixed effects
Fiscal year fixed effects
R2
Standard errors appear in parentheses. Significant at 1% (***), 5% (**) and 10% (*) levels.
33
Table 6
Impact of asset restrictions on profitability and risk
The table shows fixed effects regression estimates of the profitability of art museums as a
function of asset composition and size. The sample includes 129 private U.S. art museums
between 1999-2013. The museum return on assets (ROA) equals all non-investing revenue,
minus all non-investing expenses, divided by non-investment assets. The investing ROA equals
the net increase in investment assets divided by the sum of investment securities plus other
investments. Both ROA variables are compounded continuously to reduce the importance of
extreme values. Data are obtained from museums’ U.S. Internal Revenue Service Form 990
filings.
Return measures
Risk measures
Dependent variable:
Museum
ROA
Investing
ROA
Museum
ROA
squared
Investing
ROA
squared
Temporarily restricted assets / total assets
0.121
(0.084)
0.013
(0.148)
- 0.295
(0.286)
- 2.653
(1.596)
Permanently restricted assets / total assets
- 0.121
(0.105)
- 0.500 ***
(0.171)
- 0.877 **
(0.360)
- 12.309 ***
(1.834)
Museum size
(log of program service revenue)
- 0.012
(0.019)
- 0.114 ***
(0.031)
- 0.048
(0.066)
- 0.745 **
(0.337)
- 0.307 ***
(0.089)
0.504 ***
(0.156)
- 1.032 ***
(0.303)
2.663
(1.677)
0.024
(0.098)
-0.076
(0.187)
-0.462
(0.332)
-2.250
(2.007)
1,657
Yes
Yes
0.29
1,504
Yes
Yes
0.49
1,657
Yes
Yes
0.21
1,504
Yes
Yes
0.22
Fixed assets / total assets
Leverage
Museum-year observations
Museum fixed effects
Fiscal year fixed effects
R2
Standard errors appear in parentheses. Significant at 1% (***), 5% (**) and 10% (*) levels.
34
100%
90%
Percent of invested capital
80%
70%
Unrestricted
Temporarily
restricted
Permanently
restricted
Liabilities
60%
50%
40%
30%
20%
10%
0%
1999
2001
2000
2003
2002
2005
2004
2007
2006
2009
2008
2011
2010
2013
2012
Figure 1
Total capital invested in the art museum industry, by type
The figure shows the aggregate amount of capital invested in the 129 museums in the sample for
each year between 1999 and 2013. The data are displayed in four categories that sum up to 100%
of the total assets of the museums. Data are obtained from museums’ U.S. Internal Revenue
Service Form 990 filings.
35